1
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Stirbet A, Guo Y, Lazár D, Govindjee G. From leaf to multiscale models of photosynthesis: applications and challenges for crop improvement. PHOTOSYNTHESIS RESEARCH 2024; 161:21-49. [PMID: 38619700 DOI: 10.1007/s11120-024-01083-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 01/29/2024] [Indexed: 04/16/2024]
Abstract
To keep up with the growth of human population and to circumvent deleterious effects of global climate change, it is essential to enhance crop yield to achieve higher production. Here we review mathematical models of oxygenic photosynthesis that are extensively used, and discuss in depth a subset that accounts for diverse approaches providing solutions to our objective. These include models (1) to study different ways to enhance photosynthesis, such as fine-tuning antenna size, photoprotection and electron transport; (2) to bioengineer carbon metabolism; and (3) to evaluate the interactions between the process of photosynthesis and the seasonal crop dynamics, or those that have included statistical whole-genome prediction methods to quantify the impact of photosynthesis traits on the improvement of crop yield. We conclude by emphasizing that the results obtained in these studies clearly demonstrate that mathematical modelling is a key tool to examine different approaches to improve photosynthesis for better productivity, while effective multiscale crop models, especially those that also include remote sensing data, are indispensable to verify different strategies to obtain maximized crop yields.
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Affiliation(s)
| | - Ya Guo
- Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education Jiangnan University, Wuxi, 214122, China
| | - Dušan Lazár
- Department of Biophysics, Faculty of Science, Palacký Univesity, Šlechtitelů 27, 78371, Olomouc, Czech Republic
| | - Govindjee Govindjee
- Department of Biochemistry, Department of Plant Biology, and the Center of Biophysics & Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
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2
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Velluet J, Noce AD, Letort V. Practical Identifiability of Plant Growth Models: A Unifying Framework and Its Specification for Three Local Indices. PLANT PHENOMICS (WASHINGTON, D.C.) 2024; 6:0133. [PMID: 38347917 PMCID: PMC10860401 DOI: 10.34133/plantphenomics.0133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 12/12/2023] [Indexed: 02/15/2024]
Abstract
Amid the rise of machine learning models, a substantial portion of plant growth models remains mechanistic, seeking to capture an in-depth understanding of the underlying phenomena governing the system's dynamics. The development of these models typically involves parameter estimation from experimental data. Ensuring that the estimated parameters align closely with their respective "true" values is crucial since they hold biological interpretation, leading to the challenge of uniqueness in the solutions. Structural identifiability analysis addresses this issue under the assumption of perfect observations of system dynamics, whereas practical identifiability considers limited measurements and the accompanying noise. In the literature, definitions for structural identifiability vary only slightly among authors, whereas the concept and quantification of practical identifiability lack consensus, with several indices coexisting. In this work, we provide a unified framework for studying identifiability, accommodating different definitions that need to be instantiated depending on each application case. In a more applicative second step, we focus on three widely used methods for quantifying practical identifiability: collinearity indices, profile likelihood, and average relative error. We show the limitations of their local versions, and we propose a new risk index built on the profile likelihood-based confidence intervals. We illustrate the usefulness of these concepts for plant growth modeling using a discrete-time individual plant growth model, LNAS, and a continuous-time plant population epidemics model. Through this work, we aim to underline the significance of identifiability analysis as a complement to any parameter estimation study and offer guidance to the modeler.
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Affiliation(s)
| | - Antonin Della Noce
- MICS Laboratory, CentraleSupelec, Paris-Saclay University, Gif-sur-Yvette, France
| | - Véronique Letort
- MICS Laboratory, CentraleSupelec, Paris-Saclay University, Gif-sur-Yvette, France
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3
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Hunt H, Leape S, Sidhu JS, Ajmera I, Lynch JP, Ratcliffe RG, Sweetlove LJ. A role for fermentation in aerobic conditions as revealed by computational analysis of maize root metabolism during growth by cell elongation. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 116:1553-1570. [PMID: 37831626 DOI: 10.1111/tpj.16478] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/07/2023] [Accepted: 09/11/2023] [Indexed: 10/15/2023]
Abstract
The root is a well-studied example of cell specialisation, yet little is known about the metabolism that supports the transport functions and growth of different root cell types. To address this, we used computational modelling to study metabolism in the elongation zone of a maize lateral root. A functional-structural model captured the cell-anatomical features of the root and modelled how they changed as the root elongated. From these data, we derived constraints for a flux balance analysis model that predicted metabolic fluxes of the 11 concentric rings of cells in the root. We discovered a distinct metabolic flux pattern in the cortical cell rings, endodermis and pericycle (but absent in the epidermis) that involved a high rate of glycolysis and production of the fermentation end-products lactate and ethanol. This aerobic fermentation was confirmed experimentally by metabolite analysis. The use of fermentation in the model was not obligatory but was the most efficient way to meet the specific demands for energy, reducing power and carbon skeletons of expanding cells. Cytosolic acidification was avoided in the fermentative mode due to the substantial consumption of protons by lipid synthesis. These results expand our understanding of fermentative metabolism beyond that of hypoxic niches and suggest that fermentation could play an important role in the metabolism of aerobic tissues.
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Affiliation(s)
- Hilary Hunt
- Department of Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK
| | - Stefan Leape
- Department of Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK
| | - Jagdeep Singh Sidhu
- Department of Plant Science, The Pennsylvania State University, University Park, Pennsylvania, 16802, USA
| | - Ishan Ajmera
- Department of Plant Science, The Pennsylvania State University, University Park, Pennsylvania, 16802, USA
| | - Jonathan P Lynch
- Department of Plant Science, The Pennsylvania State University, University Park, Pennsylvania, 16802, USA
| | - R George Ratcliffe
- Department of Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK
| | - Lee J Sweetlove
- Department of Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK
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4
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Konagaya A, Gutmann G, Zhang Y. Co-creation environment with cloud virtual reality and real-time artificial intelligence toward the design of molecular robots. J Integr Bioinform 2023; 20:jib-2022-0017. [PMID: 36194394 PMCID: PMC10063180 DOI: 10.1515/jib-2022-0017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 08/31/2022] [Accepted: 09/07/2022] [Indexed: 11/15/2022] Open
Abstract
This paper describes the design philosophy for our cloud-based virtual reality (VR) co-creation environment (CCE) for molecular modeling. Using interactive VR simulation can provide enhanced perspectives in molecular modeling for intuitive live demonstration and experimentation in the CCE. Then the use of the CCE can enhance knowledge creation by bringing people together to share and create ideas or knowledge that may not emerge otherwise. Our prototype CCE discussed here, which was developed to demonstrate our design philosophy, has already enabled multiple members to log in and touch virtual molecules running on a cloud server with no noticeable network latency via real-time artificial intelligence techniques. The CCE plays an essential role in the rational design of molecular robot parts, which consist of bio-molecules such as DNA and protein molecules.
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Affiliation(s)
- Akihiko Konagaya
- Molecular Robotics Research Institute, Co., Ltd., 4259-3, Nagatsuta, Midori, Yokohama, Japan
- Keisen University, 2-10-1, Minamino, Tama, Tokyo, Japan
| | - Gregory Gutmann
- Molecular Robotics Research Institute, Co., Ltd., 4259-3, Nagatsuta, Midori, Yokohama, Japan
| | - Yuhui Zhang
- Molecular Robotics Research Institute, Co., Ltd., 4259-3, Nagatsuta, Midori, Yokohama, Japan
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5
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Iqbal WA, Lisitsa A, Kapralov MV. Predicting plant Rubisco kinetics from RbcL sequence data using machine learning. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:638-650. [PMID: 36094849 PMCID: PMC9833099 DOI: 10.1093/jxb/erac368] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 09/12/2022] [Indexed: 06/15/2023]
Abstract
Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) is responsible for the conversion of atmospheric CO2 to organic carbon during photosynthesis, and often acts as a rate limiting step in the later process. Screening the natural diversity of Rubisco kinetics is the main strategy used to find better Rubisco enzymes for crop engineering efforts. Here, we demonstrate the use of Gaussian processes (GPs), a family of Bayesian models, coupled with protein encoding schemes, for predicting Rubisco kinetics from Rubisco large subunit (RbcL) sequence data. GPs trained on published experimentally obtained Rubisco kinetic datasets were applied to over 9000 sequences encoding RbcL to predict Rubisco kinetic parameters. Notably, our predicted kinetic values were in agreement with known trends, e.g. higher carboxylation turnover rates (Kcat) for Rubisco enzymes from C4 or crassulacean acid metabolism (CAM) species, compared with those found in C3 species. This is the first study demonstrating machine learning approaches as a tool for screening and predicting Rubisco kinetics, which could be applied to other enzymes.
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Affiliation(s)
- Wasim A Iqbal
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom
| | - Alexei Lisitsa
- Department of Computer Science, University of Liverpool, Liverpool, L69 3BX, United Kingdom
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6
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Gangwar T, Susko AQ, Baranova S, Guala M, Smith KP, Heuschele DJ. Multi-scale modelling predicts plant stem bending behaviour in response to wind to inform lodging resistance. ROYAL SOCIETY OPEN SCIENCE 2023; 10:221410. [PMID: 36636313 PMCID: PMC9810429 DOI: 10.1098/rsos.221410] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 11/25/2022] [Indexed: 06/17/2023]
Abstract
Lodging impedes the successful cultivation of cereal crops. Complex anatomy, morphology and environmental interactions make identifying reliable and measurable traits for breeding challenging. Therefore, we present a unique collaboration among disciplines for plant science, modelling and simulations, and experimental fluid dynamics in a broader context of breeding lodging resilient wheat and oat. We ran comprehensive wind tunnel experiments to quantify the stem bending behaviour of both cereals under controlled aerodynamic conditions. Measured phenotypes from experiments concluded that the wheat stems response is stiffer than the oat. However, these observations did not in themselves establish causal relationships of this observed behaviour with the physical traits of the plants. To further investigate we created an independent finite-element simulation framework integrating our recently developed multi-scale material modelling approach to predict the mechanical response of wheat and oat stems. All the input parameters including chemical composition, tissue characteristics and plant morphology have a strong physiological meaning in the hierarchical organization of plants, and the framework is free from empirical parameter tuning. This feature of our simulation framework reveals the multi-scale origin of the observed wide differences in the stem strength of both cereals that would not have been possible with purely experimental approach.
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Affiliation(s)
- Tarun Gangwar
- Department of Civil, Environmental, and Geo-Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Alexander Q. Susko
- Agronomy and Plant Genetics, University of Minnesota, Twin Cities, MN, USA
| | - Svetlana Baranova
- Department of Civil, Environmental, and Geo-Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Michele Guala
- Department of Civil, Environmental, and Geo-Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Kevin P. Smith
- Agronomy and Plant Genetics, University of Minnesota, Twin Cities, MN, USA
| | - D. Jo Heuschele
- Agronomy and Plant Genetics, University of Minnesota, Twin Cities, MN, USA
- Plant Science Research Unit, USDA – Agricultural Research Services, St. Paul, MN, USA
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7
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Raines CA. Improving plant productivity by re-tuning the regeneration of RuBP in the Calvin-Benson-Bassham cycle. THE NEW PHYTOLOGIST 2022; 236:350-356. [PMID: 35860861 PMCID: PMC9833393 DOI: 10.1111/nph.18394] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 06/30/2022] [Indexed: 05/03/2023]
Abstract
The Calvin-Benson-Bassham (CBB) cycle is arguably the most important pathway on earth, capturing CO2 from the atmosphere and converting it into organic molecules, providing the basis for life on our planet. This cycle has been intensively studied over the 50 yr since it was elucidated, and it is highly conserved across nature, from cyanobacteria to the largest of our land plants. Eight out of the 11 enzymes in this cycle catalyse the regeneration of ribulose-1-5 bisphosphate (RuBP), the CO2 acceptor molecule. The potential to manipulate RuBP regeneration to improve photosynthesis has been demonstrated in a number of plant species, and the development of new technologies, such as omics and synthetic biology provides exciting future opportunities to improve photosynthesis and increase crop yields.
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Affiliation(s)
- Christine A. Raines
- School of Life SciencesUniversity of EssexWivenhoe ParkColchesterEssexCO3 4JEUK
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8
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Senger E, Osorio S, Olbricht K, Shaw P, Denoyes B, Davik J, Predieri S, Karhu S, Raubach S, Lippi N, Höfer M, Cockerton H, Pradal C, Kafkas E, Litthauer S, Amaya I, Usadel B, Mezzetti B. Towards smart and sustainable development of modern berry cultivars in Europe. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 111:1238-1251. [PMID: 35751152 DOI: 10.1111/tpj.15876] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 06/15/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
Fresh berries are a popular and important component of the human diet. The demand for high-quality berries and sustainable production methods is increasing globally, challenging breeders to develop modern berry cultivars that fulfill all desired characteristics. Since 1994, research projects have characterized genetic resources, developed modern tools for high-throughput screening, and published data in publicly available repositories. However, the key findings of different disciplines are rarely linked together, and only a limited range of traits and genotypes has been investigated. The Horizon2020 project BreedingValue will address these challenges by studying a broader panel of strawberry, raspberry and blueberry genotypes in detail, in order to recover the lost genetic diversity that has limited the aroma and flavor intensity of recent cultivars. We will combine metabolic analysis with sensory panel tests and surveys to identify the key components of taste, flavor and aroma in berries across Europe, leading to a high-resolution map of quality requirements for future berry cultivars. Traits linked to berry yields and the effect of environmental stress will be investigated using modern image analysis methods and modeling. We will also use genetic analysis to determine the genetic basis of complex traits for the development and optimization of modern breeding technologies, such as molecular marker arrays, genomic selection and genome-wide association studies. Finally, the results, raw data and metadata will be made publicly available on the open platform Germinate in order to meet FAIR data principles and provide the basis for sustainable research in the future.
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Affiliation(s)
- Elisa Senger
- Institute of Bio- and Geosciences, IBG-4 Bioinformatics, BioSC, CEPLAS, Forschungszentrum Jülich, Jülich, Germany
| | - Sonia Osorio
- Departamento de Biología Molecular y Bioquímica, Instituto de Hortofruticultura Subtropical y Mediterránea 'La Mayora', Universidad de Málaga-Consejo Superior de Investigaciones Científicas, Campus de Teatinos, Málaga, Spain
| | | | - Paul Shaw
- Department of Information and Computational Sciences, The James Hutton Institute, Invergowrie, Scotland, UK
| | - Béatrice Denoyes
- Université de Bordeaux, UMR BFP, INRAE, Villenave d'Ornon, France
| | - Jahn Davik
- Department of Molecular Plant Biology, Norwegian Institute of Bioeconomy Research (NIBIO), Ås, Norway
| | - Stefano Predieri
- Bio-Agrofood Department, Institute for Bioeconomy, IBE-CNR, Italian National Research Council, Bologna, Italy
| | - Saila Karhu
- Natural Resources Institute Finland (Luke), Turku, Finland
| | - Sebastian Raubach
- Department of Information and Computational Sciences, The James Hutton Institute, Invergowrie, Scotland, UK
| | - Nico Lippi
- Bio-Agrofood Department, Institute for Bioeconomy, IBE-CNR, Italian National Research Council, Bologna, Italy
| | - Monika Höfer
- Institute of Breeding Research on Fruit Crops, Federal Research Centre for Cultivated Plants (JKI), Dresden, Germany
| | - Helen Cockerton
- Genetics, Genomics and Breeding Department, NIAB, East Malling, UK
| | - Christophe Pradal
- CIRAD and UMR AGAP Institute, Montpellier, France
- INRIA and LIRMM, University Montpellier, CNRS, Montpellier, France
| | - Ebru Kafkas
- Department of Horticulture, Faculty of Agriculture, Çukurova University, Balcalı, Adana, Turkey
| | | | - Iraida Amaya
- Unidad Asociada deI + D + i IFAPA-CSIC Biotecnología y Mejora en Fresa, Málaga, Spain
- Laboratorio de Genómica y Biotecnología, Centro IFAPA de Málaga, Instituto Andaluz de Investigación y Formación Agraria y Pesquera, Málaga, Spain
| | - Björn Usadel
- Institute of Bio- and Geosciences, IBG-4 Bioinformatics, BioSC, CEPLAS, Forschungszentrum Jülich, Jülich, Germany
- Institute for Biological Data Science, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Bruno Mezzetti
- Department of Agricultural, Food and Environmental Sciences, Università Politecnica delle Marche, Ancona, Italy
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9
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Rangarajan H, Hadka D, Reed P, Lynch JP. Multi-objective optimization of root phenotypes for nutrient capture using evolutionary algorithms. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 111:38-53. [PMID: 35426959 PMCID: PMC9544003 DOI: 10.1111/tpj.15774] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 04/05/2022] [Accepted: 04/10/2022] [Indexed: 05/11/2023]
Abstract
Root phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three-dimensional functional-structural plant model, SimRoot, to the Borg Multi-Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade-offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non-mobile nutrients and for maize (a monocot) and bean (a dicot). Functional-structural plant models can be used with multi-objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.
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Affiliation(s)
- Harini Rangarajan
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
| | | | - Patrick Reed
- Civil and Environmental EngineeringCornell UniversityIthacaNew YorkUSA
| | - Jonathan P. Lynch
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
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10
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Schnepf A, Leitner D, Bodner G, Javaux M. Editorial: Benchmarking 3D-Models of Root Growth, Architecture and Functioning. FRONTIERS IN PLANT SCIENCE 2022; 13:902587. [PMID: 35720543 PMCID: PMC9199489 DOI: 10.3389/fpls.2022.902587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 04/13/2022] [Indexed: 06/15/2023]
Affiliation(s)
- Andrea Schnepf
- Institute of Bio-Geosciences (IBG-3, Agrosphere), Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Daniel Leitner
- Simulationswerkstatt – Services in Computational Sciences, Linz, Austria
| | - Gernot Bodner
- Department of Crop Sciences, Division of Agronomy, University of Natural Resources and Life Sciences BOKU Vienna, Tulln an der Donau, Austria
| | - Mathieu Javaux
- Institute of Bio-Geosciences (IBG-3, Agrosphere), Forschungszentrum Jülich GmbH, Jülich, Germany
- Earth and Life Institute, Université Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium
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11
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Xue X, Wang J, Shukla D, Cheung LS, Chen LQ. When SWEETs Turn Tweens: Updates and Perspectives. ANNUAL REVIEW OF PLANT BIOLOGY 2022; 73:379-403. [PMID: 34910586 DOI: 10.1146/annurev-arplant-070621-093907] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Sugar translocation between cells and between subcellular compartments in plants requires either plasmodesmata or a diverse array of sugar transporters. Interactions between plants and associated microorganisms also depend on sugar transporters. The sugars will eventually be exported transporter (SWEET) family is made up of conserved and essential transporters involved in many critical biological processes. The functional significance and small size of these proteins have motivated crystallographers to successfully capture several structures of SWEETs and their bacterial homologs in different conformations. These studies together with molecular dynamics simulations have provided unprecedented insights into sugar transport mechanisms in general and into substrate recognition of glucose and sucrose in particular. This review summarizes our current understanding of the SWEET family, from the atomic to the whole-plant level. We cover methods used for their characterization, theories about their evolutionary origins, biochemical properties, physiological functions, and regulation. We also include perspectives on the future work needed to translate basic research into higher crop yields.
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Affiliation(s)
- Xueyi Xue
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA;
| | - Jiang Wang
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA;
| | - Diwakar Shukla
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Lily S Cheung
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Li-Qing Chen
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA;
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12
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Boatwright JL, Sapkota S, Myers M, Kumar N, Cox A, Jordan KE, Kresovich S. Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum Using Multiscale Phenotypes. FRONTIERS IN PLANT SCIENCE 2022; 13:790005. [PMID: 35665170 PMCID: PMC9159972 DOI: 10.3389/fpls.2022.790005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 04/19/2022] [Indexed: 06/15/2023]
Abstract
Carbon partitioning in plants may be viewed as a dynamic process composed of the many interactions between sources and sinks. The accumulation and distribution of fixed carbon is not dictated simply by the sink strength and number but is dependent upon the source, pathways, and interactions of the system. As such, the study of carbon partitioning through perturbations to the system or through focus on individual traits may fail to produce actionable developments or a comprehensive understanding of the mechanisms underlying this complex process. Using the recently published sorghum carbon-partitioning panel, we collected both macroscale phenotypic characteristics such as plant height, above-ground biomass, and dry weight along with microscale compositional traits to deconvolute the carbon-partitioning pathways in this multipurpose crop. Multivariate analyses of traits resulted in the identification of numerous loci associated with several distinct carbon-partitioning traits, which putatively regulate sugar content, manganese homeostasis, and nitrate transportation. Using a multivariate adaptive shrinkage approach, we identified several loci associated with multiple traits suggesting that pleiotropic and/or interactive effects may positively influence multiple carbon-partitioning traits, or these overlaps may represent molecular switches mediating basal carbon allocating or partitioning networks. Conversely, we also identify a carbon tradeoff where reduced lignin content is associated with increased sugar content. The results presented here support previous studies demonstrating the convoluted nature of carbon partitioning in sorghum and emphasize the importance of taking a holistic approach to the study of carbon partitioning by utilizing multiscale phenotypes.
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Affiliation(s)
- J. Lucas Boatwright
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
| | - Sirjan Sapkota
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
| | - Matthew Myers
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
| | - Neeraj Kumar
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
| | - Alex Cox
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
| | - Kathleen E. Jordan
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
| | - Stephen Kresovich
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Feed the Future Innovation Lab for Crop Improvement, Cornell University, Ithaca, NY, United States
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13
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Lombardo SD, Wangsaputra IF, Menche J, Stevens A. Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease. Genes (Basel) 2022; 13:764. [PMID: 35627149 PMCID: PMC9141211 DOI: 10.3390/genes13050764] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/04/2022] [Accepted: 04/13/2022] [Indexed: 02/04/2023] Open
Abstract
The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.
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Affiliation(s)
- Salvo Danilo Lombardo
- Max Perutz Labs, Department of Structural and Computational Biology, University of Vienna, 1030 Vienna, Austria;
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1030 Vienna, Austria
| | - Ivan Fernando Wangsaputra
- Maternal and Fetal Health Research Group, Division of Developmental Biology and Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9WL, UK;
| | - Jörg Menche
- Max Perutz Labs, Department of Structural and Computational Biology, University of Vienna, 1030 Vienna, Austria;
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1030 Vienna, Austria
- Faculty of Mathematics, University of Vienna, 1030 Vienna, Austria
| | - Adam Stevens
- Maternal and Fetal Health Research Group, Division of Developmental Biology and Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9WL, UK;
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14
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Ndoye MS, Burridge J, Bhosale R, Grondin A, Laplaze L. Root traits for low input agroecosystems in Africa: Lessons from three case studies. PLANT, CELL & ENVIRONMENT 2022; 45:637-649. [PMID: 35037274 DOI: 10.1111/pce.14256] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 12/09/2021] [Indexed: 06/14/2023]
Abstract
In many regions across Africa, agriculture is largely based on low-input and small-holder farming systems that use little inorganic fertilisers and have limited access to irrigation and mechanisation. Improving agricultural practices and developing new cultivars adapted to these environments, where production already suffers from climate change, is a major priority for food security. Here, we illustrate how breeding for specific root traits could improve crop resilience in Africa using three case studies covering very contrasting low-input agroecosystems. We first review how greater basal root whorl number and longer and denser root hairs increased P acquisition efficiency and yield in common bean in South East Africa. We then discuss how water-saving strategies, root hair density and deep root growth could be targeted to improve sorghum and pearl millet yield in West Africa. Finally, we evaluate how breeding for denser root systems in the topsoil and interactions with arbuscular mycorrhizal fungi could be mobilised to optimise water-saving alternate wetting and drying practices in West African rice agroecosystems. We conclude with a discussion on how to evaluate the utility of root traits and how to make root trait selection feasible for breeders so that improved varieties can be made available to farmers through participatory approaches.
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Affiliation(s)
- Mame S Ndoye
- CERAAS, Thies Escale, Thies, Senegal
- LMI LAPSE, Centre de Recherche ISRA/IRD de Bel Air, Dakar, Senegal
- UMR DIADE, Université de Montpellier, IRD, CIRAD, Montpellier, France
| | - James Burridge
- UMR DIADE, Université de Montpellier, IRD, CIRAD, Montpellier, France
| | - Rahul Bhosale
- Future Food Beacon of Excellence and School of Biosciences, University of Nottingham, Nottingham, UK
| | - Alexandre Grondin
- CERAAS, Thies Escale, Thies, Senegal
- LMI LAPSE, Centre de Recherche ISRA/IRD de Bel Air, Dakar, Senegal
- UMR DIADE, Université de Montpellier, IRD, CIRAD, Montpellier, France
| | - Laurent Laplaze
- LMI LAPSE, Centre de Recherche ISRA/IRD de Bel Air, Dakar, Senegal
- UMR DIADE, Université de Montpellier, IRD, CIRAD, Montpellier, France
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15
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Lynch JP, Mooney SJ, Strock CF, Schneider HM. Future roots for future soils. PLANT, CELL & ENVIRONMENT 2022; 45:620-636. [PMID: 34725839 PMCID: PMC9299599 DOI: 10.1111/pce.14213] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 09/05/2021] [Accepted: 10/06/2021] [Indexed: 05/12/2023]
Abstract
Mechanical impedance constrains root growth in most soils. Crop cultivation changed the impedance characteristics of native soils, through topsoil erosion, loss of organic matter, disruption of soil structure and loss of biopores. Increasing adoption of Conservation Agriculture in high-input agroecosystems is returning cultivated soils to the soil impedance characteristics of native soils, but in the low-input agroecosystems characteristic of developing nations, ongoing soil degradation is generating more challenging environments for root growth. We propose that root phenotypes have evolved to adapt to the altered impedance characteristics of cultivated soil during crop domestication. The diverging trajectories of soils under Conservation Agriculture and low-input agroecosystems have implications for strategies to develop crops to meet global needs under climate change. We present several root ideotypes as breeding targets under the impedance regimes of both high-input and low-input agroecosystems, as well as a set of root phenotypes that should be useful in both scenarios. We argue that a 'whole plant in whole soil' perspective will be useful in guiding the development of future crops for future soils.
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Affiliation(s)
- Jonathan P. Lynch
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
| | - Sacha J. Mooney
- School of BiosciencesUniversity of NottinghamLeicestershireUK
| | - Christopher F. Strock
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
| | - Hannah M. Schneider
- Centre for Crop Systems AnalysisWageningen University & ResearchWageningenThe Netherlands
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16
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Ajmera I, Henry A, Radanielson AM, Klein SP, Ianevski A, Bennett MJ, Band LR, Lynch JP. Integrated root phenotypes for improved rice performance under low nitrogen availability. PLANT, CELL & ENVIRONMENT 2022; 45:805-822. [PMID: 35141925 PMCID: PMC9303783 DOI: 10.1111/pce.14284] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 10/27/2021] [Accepted: 10/30/2021] [Indexed: 05/06/2023]
Abstract
Greater nitrogen efficiency would substantially reduce the economic, energy and environmental costs of rice production. We hypothesized that synergistic balancing of the costs and benefits for soil exploration among root architectural phenes is beneficial under suboptimal nitrogen availability. An enhanced implementation of the functional-structural model OpenSimRoot for rice integrated with the ORYZA_v3 crop model was used to evaluate the utility of combinations of root architectural phenes, namely nodal root angle, the proportion of smaller diameter nodal roots, nodal root number; and L-type and S-type lateral branching densities, for plant growth under low nitrogen. Multiple integrated root phenotypes were identified with greater shoot biomass under low nitrogen than the reference cultivar IR64. The superiority of these phenotypes was due to synergism among root phenes rather than the expected additive effects of phene states. Representative optimal phenotypes were predicted to have up to 80% greater grain yield with low N supply in the rainfed dry direct-seeded agroecosystem over future weather conditions, compared to IR64. These phenotypes merit consideration as root ideotypes for breeding rice cultivars with improved yield under rainfed dry direct-seeded conditions with limited nitrogen availability. The importance of phene synergism for the performance of integrated phenotypes has implications for crop breeding.
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Affiliation(s)
- Ishan Ajmera
- Division of Plant and Crop Sciences, School of BiosciencesUniversity of NottinghamSutton BoningtonUK
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
| | - Amelia Henry
- Strategic Innovation PlatformInternational Rice Research InstituteLos BañosLagunaPhilippines
| | - Ando M. Radanielson
- Strategic Innovation PlatformInternational Rice Research InstituteLos BañosLagunaPhilippines
- Centre for Sustainable Agricultural Systems, Institute for Life Sciences and the Environment, Toowoomba CampusUniversity of Southern QueenslandToowoombaQueenslandAustralia
| | - Stephanie P. Klein
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
| | - Aleksandr Ianevski
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiFinland
| | - Malcolm J. Bennett
- Division of Plant and Crop Sciences, School of BiosciencesUniversity of NottinghamSutton BoningtonUK
| | - Leah R. Band
- Division of Plant and Crop Sciences, School of BiosciencesUniversity of NottinghamSutton BoningtonUK
- Centre for Mathematical Medicine and Biology, School of Mathematical SciencesUniversity of NottinghamNottinghamUK
| | - Jonathan P. Lynch
- Division of Plant and Crop Sciences, School of BiosciencesUniversity of NottinghamSutton BoningtonUK
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
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17
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Strock CF, Rangarajan H, Black CK, Schäfer ED, Lynch JP. Theoretical evidence that root penetration ability interacts with soil compaction regimes to affect nitrate capture. ANNALS OF BOTANY 2022; 129:315-330. [PMID: 34850823 PMCID: PMC8835659 DOI: 10.1093/aob/mcab144] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Accepted: 11/26/2021] [Indexed: 05/14/2023]
Abstract
BACKGROUND AND AIMS Although root penetration of strong soils has been intensively studied at the scale of individual root axes, interactions between soil physical properties and soil foraging by whole plants are less clear. Here we investigate how variation in the penetration ability of distinct root classes and bulk density profiles common to real-world soils interact to affect soil foraging strategies. METHODS We utilize the functional-structural plant model 'OpenSimRoot' to simulate the growth of maize (Zea mays) root systems with variable penetration ability of axial and lateral roots in soils with (1) uniform bulk density, (2) plow pans and (3) increasing bulk density with depth. We also modify the availability and leaching of nitrate to uncover reciprocal interactions between these factors and the capture of mobile resources. KEY RESULTS Soils with plow pans and bulk density gradients affected overall size, distribution and carbon costs of the root system. Soils with high bulk density at depth impeded rooting depth and reduced leaching of nitrate, thereby improving the coincidence of nitrogen and root length. While increasing penetration ability of either axial or lateral root classes produced root systems of comparable net length, improved penetration of axial roots increased allocation of root length in deeper soil, thereby amplifying N acquisition and shoot biomass. Although enhanced penetration ability of both root classes was associated with greater root system carbon costs, the benefit to plant fitness from improved soil exploration and resource capture offset these. CONCLUSIONS While lateral roots comprise the bulk of root length, axial roots function as a scaffold determining the distribution of these laterals. In soils with high soil strength and leaching, root systems with enhanced penetration ability of axial roots have greater distribution of root length at depth, thereby improving capture of mobile resources.
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Affiliation(s)
- Christopher F Strock
- Department of Plant Science, The Pennsylvania State University, University Park, PA 16802, USA
| | - Harini Rangarajan
- Department of Plant Science, The Pennsylvania State University, University Park, PA 16802, USA
| | - Christopher K Black
- Department of Plant Science, The Pennsylvania State University, University Park, PA 16802, USA
| | - Ernst D Schäfer
- Department of Plant Science, The Pennsylvania State University, University Park, PA 16802, USA
| | - Jonathan P Lynch
- Department of Plant Science, The Pennsylvania State University, University Park, PA 16802, USA
- For correspondence. E-mail
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18
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York LM, Griffiths M, Maaz TM. Whole-plant phenotypic engineering: moving beyond ratios for multi-objective optimization of nutrient use efficiency. Curr Opin Biotechnol 2022; 75:102682. [PMID: 35104719 DOI: 10.1016/j.copbio.2022.102682] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 12/14/2021] [Accepted: 01/03/2022] [Indexed: 02/03/2023]
Abstract
Nutrient use efficiency (NUE) is typically measured as the ratio of yield to soil nutrient availability but ignores contributions of underlying plant traits. Relevant plant traits can be grouped as root acquisition efficiency, shoot radiation use efficiency, and plant metabolic efficiency. The intentional integration of these traits will lead to synergistic improvements of NUE. Recent progress in trait-focused research includes phenotyping root nutrient uptake rates and respiration, engineering reduced photorespiration, and identification of nutrient assimilation pathways. Traits need to be conceptualized in agricultural systems contexts to improve synchrony of plant demand and soil supply of nutrients, including consideration of crop mixtures. Use of simulation modeling and multi-objective optimization will allow accelerating NUE gains beyond selection for a single ratio.
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Affiliation(s)
- Larry M York
- Center for Bioenergy Innovation and Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
| | | | - Tai McClellan Maaz
- Department of Tropical Plant and Soil Sciences, University of Hawaii at Manoa, Honolulu, HI, USA
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19
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Lynch JP. Harnessing root architecture to address global challenges. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 109:415-431. [PMID: 34724260 PMCID: PMC9299910 DOI: 10.1111/tpj.15560] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/14/2021] [Accepted: 10/18/2021] [Indexed: 05/06/2023]
Abstract
Root architecture can be targeted in breeding programs to develop crops with better capture of water and nutrients. In rich nations, such crops would reduce production costs and environmental pollution and, in developing nations, they would improve food security and economic development. Crops with deeper roots would have better climate resilience while also sequestering atmospheric CO2 . Deeper rooting, which improves water and N capture, is facilitated by steeper root growth angles, fewer axial roots, reduced lateral branching, and anatomical phenotypes that reduce the metabolic cost of root tissue. Mechanical impedance, hypoxia, and Al toxicity are constraints to subsoil exploration. To improve topsoil foraging for P, K, and other shallow resources, shallower root growth angles, more axial roots, and greater lateral branching are beneficial, as are metabolically cheap roots. In high-input systems, parsimonious root phenotypes that focus on water capture may be advantageous. The growing prevalence of Conservation Agriculture is shifting the mechanical impedance characteristics of cultivated soils in ways that may favor plastic root phenotypes capable of exploiting low resistance pathways to the subsoil. Root ideotypes for many low-input systems would not be optimized for any one function, but would be resilient against an array of biotic and abiotic challenges. Root hairs, reduced metabolic cost, and developmental regulation of plasticity may be useful in all environments. The fitness landscape of integrated root phenotypes is large and complex, and hence will benefit from in silico tools. Understanding and harnessing root architecture for crop improvement is a transdisciplinary opportunity to address global challenges.
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Affiliation(s)
- Jonathan P. Lynch
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPA16802USA
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20
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Burridge JD, Grondin A, Vadez V. Optimizing Crop Water Use for Drought and Climate Change Adaptation Requires a Multi-Scale Approach. FRONTIERS IN PLANT SCIENCE 2022; 13:824720. [PMID: 35574091 PMCID: PMC9100818 DOI: 10.3389/fpls.2022.824720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 04/11/2022] [Indexed: 05/09/2023]
Abstract
Selection criteria that co-optimize water use efficiency and yield are needed to promote plant productivity in increasingly challenging and variable drought scenarios, particularly dryland cereals in the semi-arid tropics. Optimizing water use efficiency and yield fundamentally involves transpiration dynamics, where restriction of maximum transpiration rate helps to avoid early crop failure, while maximizing grain filling. Transpiration restriction can be regulated by multiple mechanisms and involves cross-organ coordination. This coordination involves complex feedbacks and feedforwards over time scales ranging from minutes to weeks, and from spatial scales ranging from cell membrane to crop canopy. Aquaporins have direct effect but various compensation and coordination pathways involve phenology, relative root and shoot growth, shoot architecture, root length distribution profile, as well as other architectural and anatomical aspects of plant form and function. We propose gravimetric phenotyping as an integrative, cross-scale solution to understand the dynamic, interwoven, and context-dependent coordination of transpiration regulation. The most fruitful breeding strategy is likely to be that which maintains focus on the phene of interest, namely, daily and season level transpiration dynamics. This direct selection approach is more precise than yield-based selection but sufficiently integrative to capture attenuating and complementary factors.
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Affiliation(s)
- James D. Burridge
- DIADE Group, Cereal Root Systems, Institute de Recherche pour le Développement/Université de Montpellier, Montpellier, France
- *Correspondence: James D. Burridge,
| | - Alexandre Grondin
- DIADE Group, Cereal Root Systems, Institute de Recherche pour le Développement/Université de Montpellier, Montpellier, France
- Adaptation des Plantes et Microorganismes Associés aux Stress Environnementaux, Laboratoire Mixte International, Dakar, Senegal
- Centre d’Étude Régional pour l’Amélioration de l’Adaptation à la Sécheresse, Thiès, Senegal
| | - Vincent Vadez
- DIADE Group, Cereal Root Systems, Institute de Recherche pour le Développement/Université de Montpellier, Montpellier, France
- Adaptation des Plantes et Microorganismes Associés aux Stress Environnementaux, Laboratoire Mixte International, Dakar, Senegal
- Centre d’Étude Régional pour l’Amélioration de l’Adaptation à la Sécheresse, Thiès, Senegal
- International Crops Research Institute for Semi-Arid Tropics (ICRISAT), Patancheru, India
- Vincent Vadez,
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21
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Yang X, Liu D, Lu H, Weston DJ, Chen JG, Muchero W, Martin S, Liu Y, Hassan MM, Yuan G, Kalluri UC, Tschaplinski TJ, Mitchell JC, Wullschleger SD, Tuskan GA. Biological Parts for Plant Biodesign to Enhance Land-Based Carbon Dioxide Removal. BIODESIGN RESEARCH 2021; 2021:9798714. [PMID: 37849951 PMCID: PMC10521660 DOI: 10.34133/2021/9798714] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 11/07/2021] [Indexed: 10/19/2023] Open
Abstract
A grand challenge facing society is climate change caused mainly by rising CO2 concentration in Earth's atmosphere. Terrestrial plants are linchpins in global carbon cycling, with a unique capability of capturing CO2 via photosynthesis and translocating captured carbon to stems, roots, and soils for long-term storage. However, many researchers postulate that existing land plants cannot meet the ambitious requirement for CO2 removal to mitigate climate change in the future due to low photosynthetic efficiency, limited carbon allocation for long-term storage, and low suitability for the bioeconomy. To address these limitations, there is an urgent need for genetic improvement of existing plants or construction of novel plant systems through biosystems design (or biodesign). Here, we summarize validated biological parts (e.g., protein-encoding genes and noncoding RNAs) for biological engineering of carbon dioxide removal (CDR) traits in terrestrial plants to accelerate land-based decarbonization in bioenergy plantations and agricultural settings and promote a vibrant bioeconomy. Specifically, we first summarize the framework of plant-based CDR (e.g., CO2 capture, translocation, storage, and conversion to value-added products). Then, we highlight some representative biological parts, with experimental evidence, in this framework. Finally, we discuss challenges and strategies for the identification and curation of biological parts for CDR engineering in plants.
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Affiliation(s)
- Xiaohan Yang
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Degao Liu
- Department of Genetics, Cell Biology and Development, Center for Precision Plant Genomics, and Center for Genome Engineering, University of Minnesota, Saint Paul, MN 55108, USA
| | - Haiwei Lu
- Department of Academic Education, Central Community College-Hastings, Hastings, NE 68902USA
| | - David J. Weston
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Jin-Gui Chen
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Wellington Muchero
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Stanton Martin
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Yang Liu
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Md Mahmudul Hassan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Guoliang Yuan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Udaya C. Kalluri
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Timothy J. Tschaplinski
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Julie C. Mitchell
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Stan D. Wullschleger
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Gerald A. Tuskan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
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22
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Chen J, Beauvoit B, Génard M, Colombié S, Moing A, Vercambre G, Gomès E, Gibon Y, Dai Z. Modelling predicts tomatoes can be bigger and sweeter if biophysical factors and transmembrane transports are fine-tuned during fruit development. THE NEW PHYTOLOGIST 2021; 230:1489-1502. [PMID: 33550584 DOI: 10.1111/nph.17260] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 01/30/2021] [Indexed: 06/12/2023]
Abstract
The trade-off between yield and quality, a major problem for the production of fleshy fruits, involves fruit expansive growth and sugar metabolism. Here we developed an integrative model by coupling a biophysical model of fleshy fruit growth processes, including water and carbon fluxes and organ expansion, with an enzyme-based kinetic model of sugar metabolism to better understand the interactions between these two processes. The integrative model was initially tested on tomato fruit, a model system for fleshy fruit. The integrative model closely simulated the biomass and major carbon metabolites of tomato fruit developing under optimal or stress conditions. The model also performed robustly when simulating the fruit size and sugar concentrations of different tomato genotypes including wild species. The validated model was used to explore ways of uncoupling the size-sweetness trade-off in fruit. Model-based virtual experiments suggested that larger sweeter tomatoes could be obtained by simultaneously manipulating certain biophysical factors and transmembrane transports. The integrative fleshy fruit model provides a promising tool to facilitate the targeted bioengineering and breeding of tomatoes and other fruits.
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Affiliation(s)
- Jinliang Chen
- INRAE, Bordeaux Science Agro, EGFV, UMR 1287, Univ. Bordeaux, Villenave d'Ornon, F-33140, France
- Beijing Key Laboratory of Grape Science and Enology and Key Laboratory of Plant Resources, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
| | - Bertrand Beauvoit
- INRAE, Biologie du Fruit et Pathologie, UMR 1332, Univ. Bordeaux, Villenave d'Ornon, F-33140, France
| | - Michel Génard
- UR 1115 Plantes et Systèmes de Culture Horticoles, INRAE, Avignon Cedex 9, F-84914, France
| | - Sophie Colombié
- INRAE, Biologie du Fruit et Pathologie, UMR 1332, Univ. Bordeaux, Villenave d'Ornon, F-33140, France
| | - Annick Moing
- INRAE, Biologie du Fruit et Pathologie, UMR 1332, Univ. Bordeaux, Villenave d'Ornon, F-33140, France
| | - Gilles Vercambre
- UR 1115 Plantes et Systèmes de Culture Horticoles, INRAE, Avignon Cedex 9, F-84914, France
| | - Eric Gomès
- INRAE, Bordeaux Science Agro, EGFV, UMR 1287, Univ. Bordeaux, Villenave d'Ornon, F-33140, France
| | - Yves Gibon
- INRAE, Biologie du Fruit et Pathologie, UMR 1332, Univ. Bordeaux, Villenave d'Ornon, F-33140, France
| | - Zhanwu Dai
- INRAE, Bordeaux Science Agro, EGFV, UMR 1287, Univ. Bordeaux, Villenave d'Ornon, F-33140, France
- Beijing Key Laboratory of Grape Science and Enology and Key Laboratory of Plant Resources, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
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23
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Coussement JR, Villers SLY, Nelissen H, Inzé D, Steppe K. Turgor-time controls grass leaf elongation rate and duration under drought stress. PLANT, CELL & ENVIRONMENT 2021; 44:1361-1378. [PMID: 33373049 DOI: 10.1111/pce.13989] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 12/17/2020] [Accepted: 12/21/2020] [Indexed: 06/12/2023]
Abstract
The process of leaf elongation in grasses is characterized by the creation and transformation of distinct cell zones. The prevailing turgor pressure within these cells is one of the key drivers for the rate at which these cells divide, expand and differentiate, processes that are heavily impacted by drought stress. In this article, a turgor-driven growth model for grass leaf elongation is presented, which combines mechanistic growth from the basis of turgor pressure with the ontogeny of the leaf. Drought-induced reductions in leaf turgor pressure result in a simultaneous inhibition of both cell expansion and differentiation, lowering elongation rate but increasing elongation duration due to the slower transitioning of cells from the dividing and elongating zone to mature cells. Leaf elongation is, therefore, governed by the magnitude of, and time spent under, growth-enabling turgor pressure, a metric which we introduce as turgor-time. Turgor-time is able to normalize growth patterns in terms of varying water availability, similar to how thermal time is used to do so under varying temperatures. Moreover, additional inclusion of temperature dependencies within our model pioneers a novel concept enabling the general expression of growth regardless of water availability or temperature.
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Affiliation(s)
- Jonas R Coussement
- Laboratory of Plant Ecology, Department of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
| | - Selwyn L Y Villers
- Laboratory of Plant Ecology, Department of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Hilde Nelissen
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Dirk Inzé
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Kathy Steppe
- Laboratory of Plant Ecology, Department of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
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24
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Environment-coupled models of leaf metabolism. Biochem Soc Trans 2021; 49:119-129. [PMID: 33492365 PMCID: PMC7925006 DOI: 10.1042/bst20200059] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 11/30/2020] [Accepted: 12/17/2020] [Indexed: 12/15/2022]
Abstract
The plant leaf is the main site of photosynthesis. This process converts light energy and inorganic nutrients into chemical energy and organic building blocks for the biosynthesis and maintenance of cellular components and to support the growth of the rest of the plant. The leaf is also the site of gas–water exchange and due to its large surface, it is particularly vulnerable to pathogen attacks. Therefore, the leaf's performance and metabolic modes are inherently determined by its interaction with the environment. Mathematical models of plant metabolism have been successfully applied to study various aspects of photosynthesis, carbon and nitrogen assimilation and metabolism, aided suggesting metabolic intervention strategies for optimized leaf performance, and gave us insights into evolutionary drivers of plant metabolism in various environments. With the increasing pressure to improve agricultural performance in current and future climates, these models have become important tools to improve our understanding of plant–environment interactions and to propel plant breeders efforts. This overview article reviews applications of large-scale metabolic models of leaf metabolism to study plant–environment interactions by means of flux-balance analysis. The presented studies are organized in two ways — by the way the environment interactions are modelled — via external constraints or data-integration and by the studied environmental interactions — abiotic or biotic.
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25
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Daloso DDM, Williams TCR. Current Challenges in Plant Systems Biology. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1346:155-170. [DOI: 10.1007/978-3-030-80352-0_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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26
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Abbai R, Singh VK, Snowdon RJ, Kumar A, Schnurbusch T. Seeking Crops with Balanced Parts for the Ideal Whole. TRENDS IN PLANT SCIENCE 2020; 25:1189-1193. [PMID: 32958388 DOI: 10.1016/j.tplants.2020.08.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Revised: 07/27/2020] [Accepted: 08/24/2020] [Indexed: 06/11/2023]
Abstract
Crop domestication and breeding considerably increased productivity over centuries but unconsciously lowered 'selfish plant behavior' or individual plant fitness. Paradoxically, enhancing individual plant fitness is mistakenly equated with crop improvement. Because agriculture relies on community performance, embracing an agroecological genetics and genomics viewpoint might maximize communal yield by matching crop genotypes to target environments.
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Affiliation(s)
- Ragavendran Abbai
- Independent HEISENBERG Research Group Plant Architecture, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
| | - Vikas K Singh
- International Rice Research Institute (IRRI), South Asia Hub, Hyderabad, India
| | - Rod J Snowdon
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Giessen, Germany
| | - Arvind Kumar
- IRRI-South Asia Regional Centre (ISARC), Varanasi, India
| | - Thorsten Schnurbusch
- Independent HEISENBERG Research Group Plant Architecture, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany; Institute of Agricultural and Nutritional Sciences, Faculty of Natural Sciences III, Martin Luther University Halle-Wittenberg, Halle, Germany.
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Gaillard M, Miao C, Schnable JC, Benes B. Voxel carving-based 3D reconstruction of sorghum identifies genetic determinants of light interception efficiency. PLANT DIRECT 2020; 4:e00255. [PMID: 33073164 PMCID: PMC7541904 DOI: 10.1002/pld3.255] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 07/09/2020] [Indexed: 05/02/2023]
Abstract
Changes in canopy architecture traits have been shown to contribute to yield increases. Optimizing both light interception and light interception efficiency of agricultural crop canopies will be essential to meeting the growing food needs. Canopy architecture is inherently three-dimensional (3D), but many approaches to measuring canopy architecture component traits treat the canopy as a two-dimensional (2D) structure to make large scale measurement, selective breeding, and gene identification logistically feasible. We develop a high throughput voxel carving strategy to reconstruct 3D representations of sorghum from a small number of RGB photos. Our approach builds on the voxel carving algorithm to allow for fully automatic reconstruction of hundreds of plants. It was employed to generate 3D reconstructions of individual plants within a sorghum association population at the late vegetative stage of development. Light interception parameters estimated from these reconstructions enabled the identification of known and previously unreported loci controlling light interception efficiency in sorghum. The approach is generalizable and scalable, and it enables 3D reconstructions from existing plant high throughput phenotyping datasets. We also propose a set of best practices to increase 3D reconstructions' accuracy.
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Affiliation(s)
- Mathieu Gaillard
- Department of Computer Graphics TechnologyPurdue UniversityWest LafayetteINUSA
| | - Chenyong Miao
- Center for Plant Science Innovation and Department of Agronomy and HorticultureUniversity of Nebraska‐LincolnLincolnNEUSA
| | - James C. Schnable
- Center for Plant Science Innovation and Department of Agronomy and HorticultureUniversity of Nebraska‐LincolnLincolnNEUSA
| | - Bedrich Benes
- Department of Computer Graphics TechnologyPurdue UniversityWest LafayetteINUSA
- Department of Computer SciencePurdue UniversityWest LafayetteINUSA
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